Ingredient-Level In Silico Analysis of Anti–Aquaporin-4 IgG–Driven Immune Signaling in Neuromyelitis Optica at UCLA Using CytoSolve®

Partner Description

University of California, Los Angeles The University of California, Los Angeles (UCLA) is a leading academic research institution with deep expertise in neuroimmunology and autoimmune disease biology. UCLA investigators focus on mechanistic, pathway-level understanding of neuromyelitis optica (NMO), particularly the role of pathogenic antibodies and immune-cell interactions within the central nervous system, to inform translational research and therapeutic innovation.

Challenge

Neuromyelitis optica is driven by antibody-mediated immune dysfunction within the central nervous system, where anti–aquaporin-4 (AQP4) IgG acts as a key pathogenic ingredient initiating inflammatory cascades. Disease progression emerges from coordinated signaling across astrocytes and multiple immune cell populations, producing cytokine-driven amplification loops that are difficult to capture using isolated pathway analysis or animal models alone. Differences between human and mammalian immune signaling further complicate translation, while the lack of a unified computational framework limited UCLA’s ability to systematically evaluate anti-AQP4 IgG–driven mechanisms across interconnected cellular contexts.

How CytoSolve® Helped

CytoSolve® supported UCLA by converting a proposed NMO signaling blueprint into an ingredient-focused, in silico systems architecture centered on anti-AQP4 IgG. Molecular pathways implicated in NMO were encoded as mechanistic computational models with explicit signaling logic, regulatory structure, and biological constraints.

These models were integrated into a multi-compartment, multi-cell framework capturing signal transduction and cross-talk among astrocytes, dendritic cells, T cells, and B cells. Anti-AQP4 IgG was explicitly modeled as a mechanistic perturbation, enabling simulation of how antibody binding propagates through immune networks to drive downstream inflammatory cascades. Cytokine-level outputs linked IgG–AQP4 interactions to activation patterns in interleukins 2, 4, 8, 10, and 13, providing a quantitative lens for interpreting immune amplification and inflammatory signatures relevant to NMO.

Key Benefits Realized

  • Ingredient-level mechanistic validation of anti-AQP4 IgG within a systems-scale immune framework.
  • Integrated representation of CNS-resident and peripheral immune cell signaling driving NMO pathology.
  • Ability to perform in silico perturbation experiments focused on antibody-driven immune activation.
  • Quantitative linkage between anti-AQP4 IgG activity and cytokine signatures including IL-2, IL-4, IL-8, IL-10, and IL-13.
  • Improved translational relevance through human immune-pathway modeling rather than animal-only inference.

Outcome

Through this ingredient analysis, UCLA gained a validated in silico framework for examining anti-AQP4 IgG as a central pathogenic driver of neuromyelitis optica. By unifying antibody activity, cross-cell immune signaling, and cytokine-level outcomes within a single computational architecture, CytoSolve® enabled a more rigorous, mechanistic understanding of NMO immune biology. The resulting platform strengthened hypothesis generation, guided experimental design, and supported prioritization of therapeutic strategies grounded in integrated, human-relevant pathway behavior.